Information extraction and dynamic evaluation of soil salinization with a remote sensing method in a typical county on the Huang-Huai-Hai Plain of China

Monitoring the dynamics of soil salinization is of great importance for agricultural production. This study selected Yucheng County, a typical county on the Huang-Huai-Hai Plain (HHHP) of China, as the study area and evaluated the spatial and temporal variation of soil salinization. Three methods, consisting of principal component analysis (PCA) transformation, tasseled cap (TC) transformation, and optimal band combination (OBC), were used to extract information from an early Landsat multispectral scanner (MSS) image from 1984, and their advantages were compared. In addition, OBC was used on a thematic mapper (TM) image from 2009. An iteratively self-organizing data analysis algorithm was used together with prior knowledge of likely classifications to interpret the MSS and TM images for data classification. Finally, a transfer matrix method was used to assess the spatial and temporal variability of soil salinization and analyze the driving factors of soil salinization. Compared to PCA transformation and OBC, TC transformation was a more effective method for extracting soil salinization information from the MSS sensor. The results indicate that a soil area of approximately 298 km² was affected by salinity in 1984 in Yucheng County, of which 5.40%, 11.96%, and 12.75% were classified as being subject to slight, moderate, and severe salinization, respectively. In 2009, the saline area was reduced to only 146 km², of which 10.70% and 3.75% were characterized by slight to moderate salinization and no severe salinization, respectively. The saline land decreased at an average rate of 6 km² per year. This decrease was probably a result of lower groundwater depth, increased organic fertilizer or crop straw in soil, changed land use type, and increased vegetation coverage.     

Factors Associated with Grassland Bird Species Richness: The Relative Roles of Grassland Area, Landscape Structure, and Prey

The factors responsible for widespread declines of grassland birds in the United States are not well understood. This study, conducted in the short-grass prairie of eastern Wyoming, was designed to investigate the relationship between variation in habitat amount, landscape heterogeneity, prey resources, and spatial variation in grassland bird species richness. We estimated bird richness over a 5-year period (1994–1998) from 29 Breeding Bird Survey locations. Estimated bird richness was modeled as a function of landscape structure surrounding survey routes using satellite-based imagery (1996) and grasshopper density and richness, a potentially important prey of grassland birds. Model specification progressed from simple to complex explanations for spatial variation in bird richness. An information-theoretic approach was used to rank and select candidate models. Our best model included measurements of habitat amount, habitat arrangement, landscape matrix, and prey diversity. Grassland bird richness was positively associated with grassland habitat; was negatively associated with habitat dispersion; positively associated with edge habitats; negatively associated with landscape matrix attributes that may restrict movement of grassland bird; and positively related to grasshopper richness. Collectively, 62% of the spatial variation in grassland bird richness was accounted for by the model (adj-R² = 0.514). These results suggest that the distribution of grassland bird species is influenced by a complex mixture of factors that include habitat area affects, landscape pattern and composition, and the availability of prey.     

Mapping Ridolfia segetum patches in sunflower crop using remote sensing

Ridolfia segetum is a frequent umbelliferous weed in sunflower crops in the Mediterranean basin. Field and remote sensing research was conducted in 2003 and 2004 over two naturally infested fields to determine the potential of multispectral imagery for discrimination and mapping of R. segetum patches in sunflower crops. The efficiency of the four wavebands blue (B), green (G), red (R) and near‐infrared (NIR), selected vegetation indices and the spectral angle mapper (SAM) classification method were studied using aerial photographs taken in the late vegetative (mid‐May), flowering (mid‐June) and senescence (mid‐July) crop growth stages. Discrimination efficiency of R. segetum patches in sunflower crops is consistently affected by their phenological stages, in this order: flowering > senescence > vegetative. In both fields, R. segetum patches were efficiently discriminated in mid‐June, corresponding to the flowering phase, by using the waveband G, the ratio R/B or SAM with overall accuracies ranging from 85% to 98%. The application of the median‐filtering algorithm to any of the classified images improved the accuracy. Our results suggest that mapping R. segetum weed patches in sunflower to implement site‐specific weed management techniques is feasible with aerial photography when images are taken from 8 to 10 weeks before harvesting.     

MapX在空间数据绑定与林业专题图制作中的应用探讨

从空间地图数据与属性数据的关联、专题图的生成各方法，就MapX在林业地理信息系统开发中空间数据绑定与专题图制作中的技术等作了简要探讨。     

渔业专题电子海图的数据结构设计

为实现渔业专题电子海图的标准化生产与应用,本文以IHO S-57国际电子海图标准为基础,通过分析海图数据模型和数据结构,以及渔业专题信息的主要内容和特点,扩展了数据集信息记录中的数据集标识字段,定义了海洋渔业专题电子海图产品的编码规则,在物标和属性类目中增加了渔业专题物标和专题属性,并添加了部分专题属性项(值),从而设计了渔业专题电子海图的数据结构。研究成果将有利于整合、共享与应用海洋渔业信息,促进渔业专题电子海图产品的研发与生产,为渔业生物资源研究与利用、渔业生产与管理以及海洋渔业经济发展等提供规范化信息服务支持。     

基于ArcGIS的林业专题图符号库的建立

在林业专题图制作中,需要用到大量不同种类的符号,这些符号的制作及符号库的建立和管理是林业制图的基础。结合林业专题图符号的制作,在遵循ArcGIS符号制作、符号库管理、符号化思想方法的基础上,阐述利用ArcGIS Style Manager创建林业专题图符号库的方法。     

ArcGIS在森林公园总体规划专题图制作中的应用

以甘肃省兰州市七里河区石佛沟国家森林公园为例,介绍ArcGIS软件在森林公园总体规划制图中的实际应用,给出成图内容和要求,并详细阐述成图过程中基础资料收集与准备,数据采集与输入,数据编辑与处理,专题图制作与输出等具体步骤。     

利用卫星遥感进行加拿大花旗松林虫害监测的研究

森林虫害监测是森林经营管理中的一个重要内容,为此作者利用陆地卫星第5号的主题成图仪数据,在加拿大不列颠哥伦比亚省卡奇河试验区对花旗松林被云杉茅卷蛾危害的状况进行了监测。试验表明,在直方均衡的基础上进行比值处理和最大概似分类,其图象处理效果比较理想。利用直升飞机航空目视调查所勾绘的虫害分布图进行对照检验,其位置和形状基本吻合,面积也达到一定的精度。这种分析方法所取得的结果,可作为虫害防治的依据。     

山区林地多季相TM影像综合分类研究

为了提高陆地卫星TM数据在山区林地的分类精度,利用4个季节的帽儿山TM数据进行植被分类,并辅助以物候特征和地面GIS专题信息 采用由简单到复杂的信息提取过程,先利用基于光谱知识的林地提取模型提取林地边界,再用有监分类方法分别进行林地和非林地内部类型信息的提取,生成多季相综合分类图 分类精度比单时相提高了19 6%     

林业专题图数字水印版权保护研究

针对林业专题图制作过程复杂、成本高、迫切需要进行版权保护的问题,分析了JPEG图像压缩的不变属性,在此基础上提出了一种DCT域数字水印算法,该算法将水印信息嵌入到JPEG格式的林业专题图像的中高频系数当中。结果表明：因为水印信息是嵌入在中高频系数上,所以不仅嵌入的水印信息不可感知性良好,而且水印的嵌入容量也有所增加;即使对加密林业专题图进行有损压缩时使用高于预设值的质量因子,此算法仍然能够完全一致地提取出嵌入的水印信息,并且对各种噪声干扰都具有较好的鲁棒性。